Foreword to the European journal of remote sensing special issue: urban remote sensing – challenges and solutions

This special issue features a collection of ten contributions focusing on urban remote sensing applications. This special issue reflects the thematic diversity and variety of urban remote sensing applications and underlines the importance of this research field. Based on the 5th EARSeL Joint Workshop “Urban Remote Sensing – Challenges & Solutions” held in Bochum, Germany in 2018 the participants were invited to contribute to this special issue. The EARSeL Joint Workshop is a new format that was first initiated in 2006 in Berlin, Germany. Further EARSeL Joint Workshops followed in 2008 in Bochum, Germany, 2010 in Ghent, Belgium, 2012 in Mykonos, Greece and 2014 in Warsaw, Poland. The composition of the participating EARSeL Special Interest Groups varied from workshop to workshop. For 2018 the EARSeL Special Interest Groups Urban Remote Sensing, 3D Remote Sensing, Developing Countries and Radar Remote Sensing agreed to organize this workshop together. High resolution data are a valuable source for urban and suburban areas and can deliver information in high geometric and semantic quality for various cities and urban agglomerations around the world. Due to accelerating urban sprawl and increasing urban population more and more topics arise where remote sensing is able to support planning and other public duties. It also helps to analyse unplanned developments, investigate climate change drivers and can help in risk mitigation plans. For these topics satellite images with very high resolution (VHR) are of great importance. Since 1999 with the first commercial VHR satellites more and more sensor systems came into orbit and offer a wide variety of different image options. Information extraction can be done in 2D and also in 3D. Parallel to the VHR imagery one also observes studies over large areas with rather coarse pixel sizes. The selection of imagery obviously is connected to the scale of the problem under investigation. This is a traditional geographic approach to select the needed data according to the needed scale

Remote Sensing of Soils for Environmental Assessment and Management.

The next generation of imaging systems integrated with complex analytical methods will revolutionize the way we inventory and manage soil resources across a wide range of scientific disciplines and application domains. This special issue highlights those systems and methods for the direct benefit of environmental professionals and students who employ imaging and geospatial information for improved understanding, management, and monitoring of soil resources

Proceedings of the International Workshop on: methods and tools for water-related adaptation to climate change and climate proofing

The workshop fits in the National Water Plan of the Netherlands’ government of which the international chapter includes the strengthening of cooperation with other delta countries, including Indonesia, Vietnam and Bangladesh and is part of the work plan of the Cooperative Programme on Water and Climate, a Netherlands’ sponsored programme with the objective to improve knowledge and capacity on the relation between water and climate change especially in developing countries and countries in transition

Challenges and Opportunities of Multimodality and Data Fusion in Remote Sensing

International audience—Remote sensing is one of the most common ways to extract relevant information about the Earth and our environment. Remote sensing acquisitions can be done by both active (synthetic aperture radar, LiDAR) and passive (optical and thermal range, multispectral and hyperspectral) devices. According to the sensor, a variety of information about the Earth's surface can be obtained. The data acquired by these sensors can provide information about the structure (optical, synthetic aperture radar), elevation (LiDAR) and material content (multi and hyperspectral) of the objects in the image. Once considered together their comple-mentarity can be helpful for characterizing land use (urban analysis, precision agriculture), damage detection (e.g., in natural disasters such as floods, hurricanes, earthquakes, oil-spills in seas), and give insights to potential exploitation of resources (oil fields, minerals). In addition, repeated acquisitions of a scene at different times allows one to monitor natural resources and environmental variables (vegetation phenology, snow cover), anthropological effects (urban sprawl, deforestation), climate changes (desertification, coastal erosion) among others. In this paper, we sketch the current opportunities and challenges related to the exploitation of multimodal data for Earth observation. This is done by leveraging the outcomes of the Data Fusion contests, organized by the IEEE Geoscience and Remote Sensing Society since 2006. We will report on the outcomes of these contests, presenting the multimodal sets of data made available to the community each year, the targeted applications and an analysis of the submitted methods and results: How was multimodality considered and integrated in the processing chain? What were the improvements/new opportunities offered by the fusion? What were the objectives to be addressed and the reported solutions? And from this, what will be the next challenges

Extension of ERIM multispectral data processing capabilities through improved data handling techniques

The improvement and extension of the capabilities of the Environmental Research Institute of Michigan processing facility in handling multispectral data are discussed. Improvements consisted of implementing hardware modifications which permitted more rapid access to the recorded data through improved numbering and indexing of such data. In addition, techniques are discussed for handling data from sources other than the ERIM M-5 and M-7 scanner systems

Foreword to the special Issue on Hyperspectral remote sensing and imaging spectroscopy

The twenty six papers in this special issue focus on the technologies of hyperspectral remote sensing (HRS)and imaging spectroscopy. HRS has emerged as a powerful tool to understand phenomena at local and global scales by virtue of imaging through a diverse range of platforms, including terrestrial in-situ imaging platforms, unmanned and manned aerial vehicles, and satellite platforms. By virtue of imaging over a wide range of spectral wavelengths, it is possible to characterize object specific properties very accurately. As a result, hyperspectral imaging (also known as imaging spectroscopy) has gained popularity for a wide variety of applications, including environment monitoring, precision agriculture, mineralogy, forestry, urban planning, and defense applications. The increased analysis capability comes at a cost—there are a variety of challenges that must be overcome for robust image analysis of such data, including high dimensionality, limited sample size for training supervised models, noise and atmospheric affects, mixed pixels, etc. The papers in this issue represent some of the recent developments in image analysis algorithms and unique applications of hyperspectral imaging data

Integrated use of LANDSAT data for state resource management

There are no author-identified significant results in this report